EP 4037463 A4 20230927 - HYBRID VISION SYSTEM FOR CROP LAND NAVIGATION
Title (en)
HYBRID VISION SYSTEM FOR CROP LAND NAVIGATION
Title (de)
HYBRIDES SICHTSYSTEM FÜR ERNTEFLÄCHENNAVIGATION
Title (fr)
SYSTÈME DE VISION HYBRIDE POUR NAVIGATION TERRESTRE DE CULTURE
Publication
Application
Priority
- US 201916593151 A 20191004
- US 2020052107 W 20200923
Abstract (en)
[origin: US2021103728A1] In an embodiment, autonomous vehicles with global positioning systems (GPS) are used for field inspection to reduce fuel and labor costs and improve reliability with increased consistency in field crop inspection. A vehicle may be programmed to traverse a field while using sensors to detect objects and operating in a first image capture mode, for example, capturing low-resolution images of objects in the field, typically crops. Under program control, machine vision techniques are used with the low-resolution images to recognize crops, non-crop plant material or undefined objects. Under program control, location data is used to correlate recognized objects with digitally stored field maps to resolve whether a particular object is in a location at which crop planting is expected or not expected. Under program control, depending on whether an object in a low-resolution digital image is recognized as a crop, and whether the object is in an expected geo-location for crops, the vehicle may cease traversing temporarily and switch to a second image capture mode, for example, capturing a high-resolution image of the object, for use in disease analysis or classification, weed analysis or classification, alert notifications or other messages, or other processing. In this manner, a field may be rapidly traversed and imaged using coarse-level, rapid techniques that require lower processing resources, storage or memory, while automatically switching to execute special processing only when necessary to resolve unexpected objects or to perform operations such as disease classification that benefit from high-resolution images and more intensive use of processing resources, storage or memory.
IPC 8 full level
A01D 34/00 (2006.01); A01M 7/00 (2006.01)
CPC (source: EP US)
A01B 79/005 (2013.01 - EP); G05D 1/0246 (2024.01 - US); G06F 18/2413 (2023.01 - US); G06F 18/285 (2023.01 - EP); G06N 20/00 (2019.01 - EP US); G06V 10/87 (2022.01 - EP US); G06V 20/10 (2022.01 - EP US); G06V 20/188 (2022.01 - US); G06V 20/56 (2022.01 - EP US); G06V 30/2504 (2022.01 - US); H04W 4/021 (2013.01 - EP US); H04W 4/38 (2018.02 - EP); H04W 4/40 (2018.02 - EP); A01B 69/001 (2013.01 - EP)
Citation (search report)
- [I] US 2017223947 A1 20170810 - GALL MICHAEL [US], et al
- [A] WO 2018136875 A1 20180726 - UNIV ILLINOIS [US]
- [A] US 2019228224 A1 20190725 - GUO CHENG-EN [US], et al
- See also references of WO 2021067080A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
DOCDB simple family (publication)
US 11238283 B2 20220201; US 2021103728 A1 20210408; AR 120137 A1 20220202; AU 2020360314 A1 20220526; CA 3155418 A1 20210408; CN 114466587 A 20220510; EP 4037463 A1 20220810; EP 4037463 A4 20230927; MX 2022004091 A 20220719; US 11765542 B2 20230919; US 2022262112 A1 20220818; US 2024007822 A1 20240104; WO 2021067080 A1 20210408
DOCDB simple family (application)
US 201916593151 A 20191004; AR P200102732 A 20201001; AU 2020360314 A 20200923; CA 3155418 A 20200923; CN 202080069956 A 20200923; EP 20871278 A 20200923; MX 2022004091 A 20200923; US 2020052107 W 20200923; US 202217589011 A 20220131; US 202318369770 A 20230918